AIMC Topic: Data Mining
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Neural Multi-Task Learning for Adverse Drug Reaction Extraction.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
A reliable and searchable knowledge database of adverse drug reactions (ADRs) is highly important and valuable for improving patient safety at the point of care. In this paper, we proposed a neural multi-task learning system, NeuroADR, to extract ADR...
Facilitating information extraction without annotated data using unsupervised and positive-unlabeled learning.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Information extraction (IE), the distillation of specific information from unstructured data, is a core task in natural language processing. For rare entities (<1% prevalence), collection of positive examples required to train a model may require an ...
Automatically classifying the evidence type of drug-drug interaction research papers as a step toward computer supported evidence curation.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
A longstanding issue with knowledge bases that discuss drug-drug interactions (DDIs) is that they are inconsistent with one another. Computerized support might help experts be more objective in assessing DDI evidence. A requirement for such systems i...
What Do Patients Care About? Mining Fine-grained Patient Concerns from Online Physician Reviews Through Computer-Assisted Multi-level Qualitative Analysis.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Online physician review (OPR) websites have been increasingly used by healthcare consumers to make informed decisions in selecting healthcare providers. However, consumer-generated online reviews are often unstructured and contain plural topics with ...
A semantic database for integrated management of image and dosimetric data in low radiation dose research in medical imaging.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Medical ionizing radiation procedures and especially medical imaging are a non negligible source of exposure to patients. Whereas the biological effects of high absorbed doses are relatively well known, the effects of low absorbed doses are still deb...
Selection of Clinical Text Features for Classifying Suicide Attempts.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Research has demonstrated cohort misclassification when studies of suicidal thoughts and behaviors (STBs) rely on ICD-9/10-CM diagnosis codes. Electronic health record (EHR) data are being explored to better identify patients, a process called EHR ph...
Applying machine learning, text mining, and spatial analysis techniques to develop a highway-railroad grade crossing consolidation model.
Accident; analysis and prevention
Jan 22, 2021
The consolidation of Highway-Railroad Grade Crossing (HRGC) is one of the effective approaches to decrease the number of crashes between trains and vehicles. From 2015-2019, there were 57 HRGC crashes at crossings in East Baton Rouge Parish (EBRP), r...
A neurodynamic optimization approach to supervised feature selection via fractional programming.
Neural networks : the official journal of the International Neural Network Society
Jan 14, 2021
Feature selection is an important issue in machine learning and data mining. Most existing feature selection methods are greedy in nature thus are prone to sub-optimality. Though some global feature selection methods based on unsupervised redundancy ...
Analyzing Surgical Treatment of Intestinal Obstruction in Children with Artificial Intelligence.
Computational and mathematical methods in medicine
Jan 11, 2021
Intestinal obstruction is a common surgical emergency in children. However, it is challenging to seek appropriate treatment for childhood ileus since many diagnostic measures suitable for adults are not applicable to children. The rapid development o...
A Comprehensive Survey on Graph Neural Networks.
IEEE transactions on neural networks and learning systems
Jan 4, 2021
Deep learning has revolutionized many machine learning tasks in recent years, ranging from image classification and video processing to speech recognition and natural language understanding. The data in these tasks are typically represented in the Eu...
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